Survival Analysis: A Self-Learning Text, Third Edition (Statistics for Biology and Health)
Author: Kleinbaum, David G.
Edition: 3rd ed. 2012
- Used Book in Good Condition
Number Of Pages: 715
Release Date: 31-08-2011
Details: Product Description An excellent introduction for all those coming to the subject for the first time. New material has been added to the second edition and the original six chapters have been modified. The previous edition sold 9500 copies world wide since its release in 1996. Based on numerous courses given by the author to students and researchers in the health sciences and is written with such readers in mind. Provides a "user-friendly" layout and includes numerous illustrations and exercises. Written in such a way so as to enable readers learn directly without the assistance of a classroom instructor. Throughout, there is an emphasis on presenting each new topic backed by real examples of a survival analysis investigation, followed up with thorough analyses of real data sets. Review From the book reviews: “The authors present fundamental and basic ideas and methods of analysis of survival/event-history data from both applications and methodological points of view. … This book is clearly written and well structured for a graduate course as well as for practitioners and consulting statisticians. … There are many good examples in this edition, and more importantly, this new edition offers additional exercises, making it a good candidate for adoption as a textbook.” (Technometrics, August, 2012) "This text is … an elementary introduction to survival analysis. It is primarily intended for self-study, but it has also proven useful as a basic text in a standard classroom course … . Each chapter starts with an Introduction, an Abbreviated outline, and Objectives, and ends with self tests, exercises and a detailed outline. Solutions to tests and exercises are also provided." (Göran Broström, Zentralblatt MATH, Vol. 1093 (19), 2006) "The most meaningful accolade that I can give to this text is that it admirably lives up to its title." Journal of the American Statistical Association, September 2006 "Imagine---a statistics textbook that actually explains things in English instead of explaining a topic by bombarding the reader with page-width equations requiring an advanced degree in Math just to read the book. If it weren't for this book, I would be really stuck." (David Britz) From the Back Cover This greatly expanded third edition of Survival Analysis- A Self-learning Text provides a highly readable description of state-of-the-art methods of analysis of survival/event-history data. This text is suitable for researchers and statisticians working in the medical and other life sciences as well as statisticians in academia who teach introductory and second-level courses on survival analysis. The third edition continues to use the unique "lecture-book" format of the first two editions with one new chapter, additional sections and clarifications to several chapters, and a revised computer appendix. The Computer Appendix, with step-by-step instructions for using the computer packages STATA, SAS, and SPSS, is expanded to include the software package R. David Kleinbaum is Professor of Epidemiology at the Rollins School of Public Health at Emory University, Atlanta, Georgia. Dr. Kleinbaum is internationally known for innovative textbooks and teaching on epidemiological methods, multiple linear regression, logistic regression, and survival analysis. He has provided extensive worldwide short-course training in over 150 short courses on statistical and epidemiological methods. He is also the author of ActivEpi (2002), an interactive computer-based instructional text on fundamentals of epidemiology, which has been used in a variety of educational environments including distance learning. Mitchel Klein is Research Assistant Professor with a joint appointment in the Department of Environmental and Occupational Health (EOH) and the Department of Epidemiology, also at the Rollins School of Public Health at Emory University. Dr. Klein is also co-author with Dr. Kleinbaum of the second edition of Logistic Regression- A Self-Learning
Package Dimensions: 10.3 x 7.3 x 1.9 inches